Correct and rapid tracheal intubation is an essential anesthesia task for surgical operations. Intubation highly depends on the subjective judgment and experience of the anesthetist. This paper proposes a statistical factor analysis approach to model the preferences of expert anesthetists to enable more accurate pre-operation judgments in cases of difficult intubation. Factor analysis combined with the mutual information between factors is used to generate a robust decision tree (DT) using Bartletts node splitting criterion for better decision-making. A tablet computer application is also developed to assist judgment. Several experiments were performed to investigate judgment accuracy and learning effects. Our proposed approach outperformed both a well-known C5.0 DT and an expert opinion derived DT. Encouraging results concerning robustness and efficiency were observed for our approach.
|Number of pages||12|
|Journal||Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A/Chung-kuo Kung Ch'eng Hsuch K'an|
|Publication status||Published - 2014 Aug 18|
All Science Journal Classification (ASJC) codes